None of those wild experiments are running on a "real", existing codebase that is more than 6 months old. The thing they don't talk about is that nobody outside these AI companies wants to vibe code with a 10 year old codebase with 2000 enterprise customers.

As you as you start to work with a codebase that you care about and need to seriously maintain, you'll see what a mess these agents make.

Related question: how do we resolve the problem that we sign a blank cheque for the autonomous agents to use however many tokens they deem necessary to respond to your request? The analogy from team management: you don't just ask someone in your team to look into something only to realize three weeks later (in the absence of any updates) that they got nowhere with a problem that you expected to take less than a day to solve.

EDIT: fixed typo

yeah I think that's exactly the disconnect - they're optimizing for a future where agents can actually be trusted to run autonomously, but we're not there yet. like the reliability just isn't good enough to justify hiding what it's doing. and honestly I'm not sure we'll get there by making the UX worse for humans who are actively supervising, because that's how you catch the edge cases that training data misses. idk, feels like they're solving tomorrow's problem while making today's harder

>The latest "meta" in AI programming appears to be agent teams (or swarms or clusters or whatever) that are designed to run for long periods of time autonomously.

more reason to catch them otherwise we have to wait a longer time. in fact hiding is more correct if the AI was less autonomous right?

If they're aiming for autonomy, why have a CLI at all? Just give us a headless mode. If I'm sitting in the terminal, it means I want to control the process. Hiding logs from an operator who’s explicitly chosen to run it manually just feels weird

Looking at it from far is simply making something large from a smaller input, so its kind of like nondeterministic decompression.

What fills the holes are best practices, what can ruin the result is wrong assumptions.

I dont see how full autonomy can work either without checkpoints along the way.

>Through that lens, these changes make more sense. They're not designing UX for a human sitting there watching the agent work. They're designing for horizontally scaling agents that work in uninterrupted stretches where the only thing that matters is the final output, not the steps it took to get there.

Even in that case they should still be logging what they're doing for later investigation/auditing if something goes wrong. Regardless of whether a human or an AI ends up doing the auditing.